Communication system and method of operation therefor

ABSTRACT

A Multiple In Multiple Out (MIMO) communication system comprises an air interface scheduler for allocating air interface resource to a plurality of user equipments transmitting to a MIMO receiver. A vector processor of the scheduler determines a receive equalizer vector for the MIMO receiver for each of a plurality of user equipments in response to a channel matrix for the user equipment. The vector processor may specifically apply singular value decomposition to the channel matrix to determine the receive equalizer vector. An orthogonality processor then determines orthogonality measures between receive equalizer vectors for different sets of user equipments. A selection processor selects a set of user equipments to be allocated a shared MIMO air interface resource in response to the orthogonality measures. By scheduling in response to orthogonality of receiver operations, a reduced interference and/or reduced receiver complexity can be achieved.

RELATED APPLICATIONS

The present application is related to the following U.S. applicationcommonly owned with this application by Motorola, Inc.: Ser. No.12/107,353, filed Apr. 22, 2008, titled “A Communication System andMethod of Operation Therefor” (attorney docket no. CML05770).

FIELD OF THE INVENTION

The invention relates to a Multiple In Multiple Out (MIMO) communicationsystem and a method of operation therefor.

BACKGROUND OF THE INVENTION

In recent years, the popularity of systems using wireless radiocommunication has increased substantially. For example, cellularcommunication systems and wireless networks have now become commonplace.The increased requirement for frequency spectrum resource has led to anincreased desire for efficient communication and especially at higherfrequencies and for higher data rates.

For example, Broadband Wireless Access systems (BWA) are becoming commonnot only in fixed deployments but also in mobile deployments. In orderto increase the capacity of such BWAs, it is desirable to increase thedata rate of the wireless communication. As a specific example, theInstitute of Electrical and Electronic Engineers (IEEE) have formed acommittee for standardizing an advanced air interface for operation inlicensed bands known as IEEE 802.16m™. The 802.16m™ standard comprisesBWA Medium Access Control (MAC) and Physical Layer (PHY) specificationsaimed at enhancing BWAs to meet the cellular layer requirements ofInternational Telecommunications Union Radiocommunications Sector(IMT-Advanced) next generation mobile networks. Similarly, WirelessLocal Area Network WLANs are becoming common not only in businessenvironments but also in domestic environments. The IEEE has formed acommittee for standardizing a very high-speed WLAN standard known asIEEE 802.11vht. It is intended that the 802.11vht™ standard will helpWLANs meet the expanding bandwidth needs of enterprise and homenetworks, as well as those of WLAN hot spots. Other popular examples ofwireless networks include the more popular names of WiFi™ and WiMAX™(corresponding to IEEE 802.11n and IEEE 802.16e)

In order to achieve high data rates over the air interface, a number ofadvanced radio techniques are employed. It has been found that insystems using open-loop approaches (i.e. without the transmitter usingknowledge of the transmit channel or the signal received at thereceiver) significant improvement can be achieved by using multipleantennas at the transmitter and the receiver. In particular, many radiocommunication systems, such as WLANs, provide for a plurality oftransmit and receive antennas to be used. Specifically, sometransmission techniques involve transmitting a data stream bysimultaneously transmitting different signals derived from the datastream from different antennas over the same communication channel. Thereceiver(s) of these techniques typically also comprise a plurality ofantennas each of which receive a combined signal corresponding to thetransmitted signals modified by the individual propagationcharacteristics of the radio link between the individual antennas. Thereceiver may then retrieve the transmitted data stream by evaluating thereceived combined signal.

Such techniques may also be used in closed loop configurations whereinthe receiver may communicate information back to the transmitterallowing this to weight the signals to the individual antennas.Specifically, data may be fed back to the transmitter to allow this toprovide a suitable beamforming. Such open and closed loop techniques areknown as Multiple Transmit Multiple Receive (MTMR) or Multiple InputMultiple Output (MIMO) schemes and can be designed to derive benefitfrom spatial diversity between the antennas in order to improvedetection. Indeed, the equivalent Signal to Noise Ratio (SNR) of thecombined signal is typically increased compared to the single antennacase thereby allowing higher channel symbol rates or higher orderconstellations. This may increase the data rate for the communicationlink and thus the capacity of the communication system.

In order to further enhance the capacity of MIMO systems, it has beenproposed that multiple users may share the same air interface resource,and specifically that two users may be allocated the same time-frequencyblock. For example, two user equipments may be allowed to simultaneouslytransmit uplink signals to a base station using the same frequencychannel.

In such systems, the scheduling of user equipments (i.e. the assignmentof time-frequency resources to user equipments) is critical for theperformance of the system, and in particular it is of the utmostimportance that the most suitable user equipments are scheduled to sharethe same time-frequency resource block.

In known systems, such scheduling may be based on the overall channelconditions or the transmit beamforming of the transmitting MIMO userequipments (the weights applied to each MIMO antenna of the transmittingMIMO user equipment). Specifically, typical scheduling algorithms seekto allocate user equipments to share time-frequency resource blocks suchthat the sharing user equipments have the most different overall channelconditions or transmit beamforming characteristics.

However, although such scheduling may provide acceptable performance inmany scenarios, it also tends to be suboptimal and have a number ofdisadvantages. For example, in many scenarios it may result in complexprocessing e.g. in order to determine the overall channel responses andto evaluate which user equipments have overall channel responses thatare most suitable for sharing resource blocks. Furthermore, in order toprovide the desired performance and differentiation between the userequipments sharing the same time-frequency resource block, complexequalization is typically necessary by the individual receivers. Forexample, as the scheduling is based on transmitter or overall channelconditions, the receiver equalization will typically need to utilizecomplex non-linear equalization in order to reduce thecross-interference between the sharing user equipments sufficiently.

Such non-linear equalization may for example include an iterativeequalization wherein received data symbols are estimated in eachiteration, with the estimated data symbols of one user equipment of aprevious iteration being used to estimate the data symbols of the otheruser equipment in the following iteration. This equalization processwill typically have to be iterated a number of times resulting in highcomputational requirements. Hence, an improved communication systemwould be advantageous and in particular a system allowing increasedflexibility, facilitated implementation, reduced complexity, reducedresource usage, increased spectral efficiency, improved and/orfacilitated multi-user operation and/or improved performance would beadvantageous.

SUMMARY OF THE INVENTION

Accordingly, the Invention seeks to preferably mitigate, alleviate oreliminate one or more of the above mentioned disadvantages singly or inany combination. According to a first aspect of the invention there isprovided a Multiple In Multiple Out, MIMO, communication systemcomprising: a vector processor for determining a receive equalizervector for a MIMO receiver for each of a plurality of user equipments inresponse to a channel matrix for the user equipment; an orthogonalityprocessor for determining, for a plurality of sets of user equipments,orthogonality measures between receive equalizer vectors of userequipments in the set, each set comprising at least two user equipmentsof the plurality of user equipments; a selection processor for selectingat least a first set of user equipments from the plurality of sets ofuser equipments to be allocated a shared MIMO air interface resource inresponse to the orthogonality measures; and an allocation processor forallocating the shared MIMO air interface resource to the first set ofuser equipments for simultaneous MIMO communication.

The invention may allow improved performance in a MIMO communicationsystem. In particular, it may in many scenarios enable, facilitate orimprove multiple user equipments reusing/sharing the same frequencyresource at the same time thereby providing an increased capacity of thecommunication system as a whole. The scheduling of users is performed inresponse to a receive equalizer vector thereby allowing the schedulingto reflect the operation of the receiver. For example, the receiveequalizer vector may represent a processing that can be performed by theMIMO receiver receiving the signals from the first set of userequipments. Thus, the scheduling may specifically seek to select userequipments that share the MIMO air interface resource such that theseare suitable for the receive processing represented by the receiveequalizer vector. Specifically, they may be selected such that userequipments sharing the air interface resource require high degrees oforthogonal receiver equalization and thus such that the receiverequalization may effectively differentiate between the received signalsfrom the individual user equipments.

The receive equalizer vector may specifically represent a simple linearreceiver equalization. Thus, user equipments may be selected to shareair interface resource such that sharing user equipments can beeffectively received using linear equalization which has high levels oforthogonality. Thus, by selecting sharing user equipments to be suitablefor low complexity linear equalization, the MIMO receiver need not applycomplex non-linear equalization. Accordingly, the computationalrequirement for the MIMO receiver may be reduced substantially.

The vector processor may specifically determine a receive equalizervector for a user equipment such that it represents the (e.g.theoretical or ideal) equalizer operation corresponding to receiving theMIMO signal from that user equipment with the highest reliability (e.g.the operation that minimizes a signal to noise/interference measure).

The receive equalizer vector may specifically represent the weightsbeing applied to each receive antenna by a linear equalizer. The linearequalizer may combine the weighted signals from each antenna, e.g. by asimple summation.

The vector processor may e.g. determine the receive equalizer vector bya singular value decomposition of the channel matrix. According to adifferent aspect of the invention, there is provided a scheduler for aMultiple In Multiple Out, MIMO, communication system, the schedulercomprising: a vector processor for determining a receive equalizervector for a MIMO receiver for each of a plurality of user equipments inresponse to a channel matrix for the user equipment; an orthogonalityprocessor for determining, for a plurality of sets of user equipments,orthogonality measures between receive equalizer vectors of userequipments in the set, each set comprising at least two user equipmentsof the plurality of user equipments; a selection processor for selectingat least a first set of user equipments from the plurality of sets ofuser equipments to be allocated a shared MIMO air interface resource inresponse to the orthogonality measures; and an allocation processor forallocating the shared MIMO air interface resource to the first set ofuser equipments for simultaneous MIMO communication.

According to a different aspect of the invention, there is provided amethod of operation for a Multiple In Multiple Out, MIMO, communicationsystem, the method comprising: determining a receive equalizer vectorfor a MIMO receiver for each of a plurality of user equipments inresponse to a channel matrix for the user equipment; determining, for aplurality of sets of user equipments, orthogonality measures betweenreceive equalizer vectors of user equipments in the set, each setcomprising at least two user equipments of the plurality of userequipments; selecting at least a first set of user equipments from theplurality of sets of user equipments to be allocated a shared MIMO airinterface resource in response to the orthogonality measures; andallocating the shared MIMO air interface resource to the first set ofuser equipments for simultaneous MIMO communication.

These and other aspects, features and advantages of the invention willbe apparent from and elucidated with reference to the embodiment(s)described hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the invention will be described, by way of example only,with reference to the drawings, in which

FIG. 1 illustrates examples of elements of a MIMO communication systemin accordance with some embodiments of the invention;

FIG. 2 illustrates examples of elements of a scheduler for a MIMOcommunication system in accordance with some embodiments of theinvention; and

FIG. 3 illustrates an example of a method of operation for a MIMOcommunication system in accordance with some embodiments of theinvention.

DETAILED DESCRIPTION OF SOME EMBODIMENTS OF THE INVENTION

The following description focuses on embodiments of the inventionapplicable to a Broadband Wireless Access system (BWA) and in particularto an IEEE 802.16e™ communication system but is also applicable to e.g.a WLAN communication system and in particular to an IEEE 802.11vht™WLAN. However, it will be appreciated that the invention is not limitedto such applications but may be applied to many other communicationsystems including for example cellular communication systems.

FIG. 1 illustrates examples of elements of a MIMO communication systemin accordance with some embodiments of the invention. In the system, theair interface resource of BWA base stations are divided into time slotsand thus air interface may be allocated in time-frequency blockscorresponding to one frequency channel in one time slot. Within eachtime-frequency block, a plurality of user equipments is allocated tosimultaneously transmit to the base station. Furthermore, the userequipments simultaneously allocated in a time slot transmit using MIMOtechniques and thus the data is transmitted from a plurality of antennasand are in the example received by a plurality of antennas. The basestations use MIMO receiver techniques to decode the data streams of theindividual user equipments sharing the time-frequency blocks andspecifically use receiver equalization techniques to differentiate thesignals from the individual user equipments.

FIG. 1 illustrates an example of elements of the communication system.FIG. 1 specifically illustrates a first and second user equipment 101,103 which are currently seeking to transmit uplink data to a basestation 105 (which in the specific example is a BWA 802.16e™ basestation). In the example, the user equipments 101, 103 represent atypically substantially larger number of user equipments that areseeking to obtain uplink resource.

In the example, the user equipments 101, 103 are BWA devices operatingin accordance with the 802.16e™ or 802.11vht™ communication standardsbut it will be appreciated that in other embodiments the user equipmentsmay be e.g. a mobile phone, a remote station, a 3G User Equipment orindeed any entity capable of communicating over an air interface of aMIMO communication system. In the example, the base station is a BWAbase station communicating in accordance with the 802.16e™ or 802.11vht™communication standards but it will be appreciated that in otherembodiments the base station may be e.g. a cellular base station or anyentity capable of supporting a plurality of user equipments over the airinterface of a MIMO communication system.

The first user equipment 101 comprises a data stream source 107 whichgenerates a data stream comprising uplink data symbols that are to betransmitted to the base station 105 over the air interface. The datastream is in the example transmitted using a MIMO technique and in thespecific example, the first user equipment 101 uses two transmitantennas 109, 111 which are coupled to the data stream source 107 viaseparate transceivers 113, 115 comprising up-converters, amplifiers etcas will be known to the person skilled in the art.

The second user equipment 103 is in the specific example identical tothe first user equipment 101 and accordingly also comprises a datastream source 117, two amplifiers 119, 121 and two transmit antennas123, 125. In the example, the base station 105 supports uplinkcommunications from a number of other user equipments (not shown) thatare similar or identical to the first and second user equipments 101,103 and which specifically also use MIMO transmission techniques foruplink transmissions.

It will be appreciated that more than two antennas may be used by eachuser equipment and indeed that the number of antennas may in someembodiments be different for different user equipments.

In the example of FIG. 1 a plurality of user equipments 101, 103 maysimultaneously transmit MIMO transmissions to the base station 105 overthe air interface. The parallel transmissions from the multiple antennas109, 111, 123, 125 of each user equipment 101, 103 are received by thebase station 105. Specifically, in the example, the base station 105comprises three antennas 127, 129, 131 that are coupled to anequalization processor 133 via individual receive amplifiers 135, 137,139. The equalization processor 133 applies receive MIMO equalizationtechniques to receive the individual data symbols transmitted from theindividual user equipments 101, 103 sharing the time-frequency resourceblock. The received data is fed to a data processor 141 which processesthe received channel symbols by for example applying error correctionetc.

In a typical communication system, a relatively large number of userequipments are supported by each base station. In the communicationsystem of FIG. 1, the base station 105 supports a number N of userequipments by dividing an air interface communication channel (carrier)into a number of sequential scheduling time slots or intervals. Each ofthe air interface communication channels may e.g. correspond to a set ofOFDM (Orthogonal Frequency Division Multiplexing) subcarriers. Thus, thesystem uses time division multiplexing to accommodate the N users in anumber of time-frequency resource blocks.

Furthermore, in the system of FIG. 1 a set comprising a plurality ofuser equipments is allocated for simultaneous transmission in eachtime-frequency resource block. The following description will focus onexamples wherein a set of two user equipments is allocated to share eachtime-frequency resource block but it will be appreciated that in otherembodiments, other numbers of user equipments may share thetime-frequency resource blocks.

The performance of the individual communications and the resultingcapacity of the communication system as a whole are highly dependent onwhich user equipments are scheduled together in each time-frequencyresource block. Specifically, as the two user equipments will introduceinterference to each other, it is important to minimize thisinterference as much as possible.

In the system of FIG. 1, the uplink scheduling for the cell served bythe base station 105 is performed by the base station 105 itself. Hence,the base station 105 comprises an air interface scheduler 143 forselecting user equipments for each scheduling resource block from the Nuser equipments requesting uplink resource. It will be appreciated thatalthough the following description focuses on an example wherein thescheduler 143 is located in the base station 105, it may in otherembodiments be located elsewhere, such as in an interconnecting network,or may e.g. be distributed over a plurality of logical or physicallocations and entities.

The scheduler 143 selects the user equipments for a given schedulingtime slot in response to orthogonality measures that indicate theorthogonality between receive equalizer vectors that reflect a linearreceiver equalization. The scheduler 143 specifically selects userequipments to share resource blocks such that the individual signalsfrom the user equipments can be effectively resolved and differentiatedby applying linear receive equalizer vectors to the received signals.Thus, the user equipments are selected such that user equipments sharinga given time-frequency resource block may require substantiallyorthogonal linear receive equalization, and thus such that the equalizervector required to maximize the received signal from one user equipmentwill automatically (due to the high degree of orthogonality) result in ahigh attenuation of the received signal from the other user equipmenttransmitting in the shared time-frequency resource block.

Furthermore, by focusing on the orthogonality of the receiverequalization rather than the orthogonality of e.g. the transmitterbeamforming, the overall channel response or the propagation channelcharacteristics, a relatively low complexity operation can be achievedwherein only a relatively low number of calculations need to beperformed for each user equipment.

Also, as the scheduling is optimized to specifically provide a highdegree of orthogonality of a linear receiver equalization, it can beassured that suitable performance can be achieved by receivers actuallyusing such linear equalization. Thus, the receiver based schedulingapproach may substantially reduce the requirements for the receiveroperation and may specifically allow a linear equalization to beperformed by the equalization processor 133. Thus, a substantialcomplexity reduction can be achieved for the receiver functionality incomparison to the complex non-linear equalization typically required forconventional scheduling approaches.

FIG. 2 illustrates some elements of the scheduler 143. The scheduler 143comprises a vector processor 201 which is arranged to determine areceive equalizer vector for the equalization processor 133 for eachuser equipment of the N user equipments that are requesting uplinkresource. The receive equalizer vector is determined in response to achannel estimate matrix for the user equipment.

For example, for the first user equipment 101, a channel matrixreflecting the propagation channel from each of the transmit antennas109, 111 to each of the receive antennas 127, 129, 131 is determined.E.g. a frequency non-selective Rayleigh fading channel is assumedresulting in the matrix comprising a single complex value for eachtransmit antenna/receive antenna combination. The channel estimates mayfor example be based on known pilot signals in the transmissions fromthe individual user equipments and possibly antennas.

The channel (estimate) matrix is then evaluated to determine the linearprocessing that may be applied to the received signals to generate areceive signal from the first user equipment 101 having a suitablecharacteristic. Specifically, the receive equalizer vector may comprisethe complex values which when multiplied with the received signal vector(i.e. the received signals from the three receive antennas 127, 129,131) and combined (specifically summed) results in the contribution fromeach path being combined (summed) coherently. For example, if theapplied transmit weights are known and the channel estimate matrix isknown, the receive equalizer vector can be determined by solving theequations that result from the constraint that the result should addcoherently.

In some embodiments, the transmit weights may not be known and thevector processor 201 may be arranged to also estimate these weights. Inparticular, for a given channel estimate matrix, the optimal transmitweights applied to the individual signals transmitted from each transmitantenna 109, 111 and the optimal receive weights applied to the signalsreceived at each individual receive antenna 127, 129, 131 may be jointlydetermined. The receive equalizer vector may then be determinedcorresponding to the determined optimal receive weights. As describedlater, this determination may specifically be performed using a singularvalue decomposition approach.

The vector processor 201 is coupled to an orthogonality processor 203which proceeds to determine orthogonality measures for sets of userequipments. The orthogonality measures are determined for the receiveequalizer vectors of the user equipments in the set.

Thus, the orthogonality processor 203 is fed all the receive equalizervectors for all N user equipments requesting uplink scheduling. It thenproceeds to divide the N user equipments into a number of sets of userequipments with each set comprising the number of user equipments thatmay share a time-frequency resource block. Thus, in the specificexample, the orthogonality processor proceeds to generate a number ofpairs of user equipments. Specifically the orthogonality processor 203can generate all possible combinations of sets comprising the desirednumber of user equipments. Thus, in the specific example, all possiblepairings of the N user equipments are determined.

For each pair, an orthogonality between the two receive equalizervectors is then determined. For example, the orthogonality may bedetermined in response to the inner product of the vectors. Forembodiments comprising more than two user equipments in each set, theorthogonality measure may e.g. be determined by summing the calculatedorthogonality measure for each possible pairing of user equipments inthe set.

Thus, the orthogonality measure has an increasing value for a higherorthogonality between the receive equalizer vectors and thus indicates ahigher orthogonality between the linear receiver operation reflected bythe receive equalizer vectors. Thus, a higher orthogonality measure isindicative of a higher probability that the actual receiver equalizationapplied to the different user equipments in the set is more orthogonal,and thus will result in a higher differentiation between the signalsfrom the different user equipments. Accordingly, a high orthogonalitymeasure for a pair of user equipments is indicative of a highlyorthogonal equalization being suitable for generating coherently addedoutput signals from the two user equipments. As a consequence, theequalizer processing required to generate a coherently added signal forone user equipment will also result in a high attenuation of the signalfrom the other user equipment.

The orthogonality processor 203 is coupled to a selection processor 205which is fed the determined orthogonality measures and which proceeds toselect at least one set of user equipments in response to theorthogonality measures. The selection processor 205 may for exampleselect the pair of user equipments which has the highest orthogonalitymeasure. As this is indicative of a possibility of a high degree ofdifferentiation being possible (even with a simple linear equalization),this set is highly suitable (or at least is the most suitable) forsharing a MIMO air interface resource, i.e. for being allocated the sameshared time-frequency resource block.

The selection processor 205 is coupled to an allocation processor 207which is fed an indication of the selected set(s) of user equipments. Itthen proceeds to allocate the MIMO air interface resource to theseset(s). Specifically, a time-frequency resource block is allocated toeach pair of user equipments selected by the selection processor 205.The allocation may be carried out in any suitable way, such as forexample by broadcasting the resource allocation on a suitable broadcastchannel.

Thus, in the described system, the allocation of shared air interfaceresource is adapted to provide a high degree of orthogonality of thereceiver equalization (rather than e.g. of the overall channelperformance or of the transmitter beamforming). This may result inattractive performance and in particular may allow a high degree ofcross-interference reduction and differentiation even when using lowcomplexity linear equalization.

In the specific example, the vector processor 201 is arranged todetermine the receive equalizer vector for a given user equipment byperforming a singular value decomposition of the channel matrix for theuser equipments.

As will be well known to the skilled person, a singular valuedecomposition is a factorization of a matrix. For example, for an m-by-nmatrix, M, whose components are either real numbers or complex numbers,a singular value decomposition may provide the factorization:

M=VΣU*

where U is an m-by-m unitary matrix, the matrix Σ is m-by-n withnonnegative numbers on the diagonal (as defined for a rectangularmatrix) and zeros off the diagonal, and V* denotes the conjugatetranspose of V which is an n-by-n unitary matrix. This factorization isknown as a singular-value decomposition of M.

It will be appreciated that different ways of implementing a singularvalue decomposition will be known to the skilled person and that anysuitable approach may be used with detracting from the invention. In thespecific case, the singular value decomposition is applied to thechannel matrix. Accordingly, the generated matrices U and V represent aset of column vectors that when multiplied with the channel matrix (onthe left and right side respectively) result in a matrix where only themain diagonal has positive values. Thus, the pair of column vectors of Uand V corresponding to one value of the diagonal represents the vectorsthat when multiplied with the channel matrix provides the overallresponse equal to the value of the diagonal. Accordingly, if the columnvector of U reflects the weighting of the transmitter antennas and thecolumn vector of V represents the linear receiver equalization, theresulting overall operation of the transmitter weighting (beamforming),the channel response and the receiver equalization corresponds to thesingle complex value of the diagonal. Thus, the column vectors U and Vare indicative of suitable coefficients for the transmitter beamformingand receiver equalization that will result in a coherent summation ofsignals being received at the output of the equalizer.

Thus, singular value decomposition provides a set of singular valuedecomposition values given by the values of the diagonal of the matrixΣ. For each of these values, there is a vector (of matrix U) thatcorresponds to the transmitter antenna weights and a vector (of matrixV) that corresponds to the receiver antenna weights. Thus, the singularvalue decomposition provided by the vector processor 201 may provideboth the (theoretically ideal) transmitter antenna weights for the givenchannel matrix as well as the (theoretically ideal) receiver antennaweights for a linear equalization comprising an addition of weightedsignals from the individual receive antennas.

Thus, in the example, the vector processor 201 may directly use one ofthe determined vectors of the matrix V as the receive equalizer vectorsince this directly indicates a suitable linear equalization operation.

Since the singular value decomposition provides more than one singularvalue (i.e. the diagonal of Σ has more than one value), there aredifferent possible transmit and receive weights that will result insuitable output signals from the linear equalizer. However, as eachsingular value of the diagonal represents the resulting signal beinggenerated by the linear equalizer, the vector processor 201 mayspecifically select the singular value (and thus the correspondingtransmitter and receiver antenna weights) that has the highest value.

In the following a more specific description using mathematical notationis provided wherein we define the transpose as T and the complexconjugate transpose as †. Capital bold face is used to indicatematrices, small boldface letters are used to indicate vectors and smallletters are used to indicate complex or real scalars.

We consider the uplink of the multi-user system, where there are Ksimultaneous transmitters (user equipments) and a single receiver (basestation). Each transmitter is equipped with N_(T) antennas to performbeam forming and the receiver has N_(R) antennas. The channel is assumedto be a frequency non-selective Rayleigh fading. The received signalvector at the receiver is then given by:

$r = {{\sum\limits_{i = 1}^{K}{\sqrt{P_{i}^{(s)}}H_{i}u_{i}s_{i}}} + n}$

where s_(i) is the transmitted symbol from the i^(th) transmitter withE[|s_(i)|²]=1, P_(i) ^((s)) denotes total transmit power of each user,H_(i) is the N_(R)×N_(T) channel matrix from the i^(th) transmitter tothe receiver and n is the noise vector with E[nn^(†)]=P^((n))I. u_(i)denotes the N_(T)×1 vector of transmit beamforming, i.e. the weightsapplied to the individual antenna signal by the transmitter.

Additionally, H_(i) can be written as:

H_(i)=V_(i)Σ_(i)U_(i) ^(†)

Thus, the channel matrix H_(i) can be factorized using singular valuedecomposition to provide suitable antenna weights for the transmitterand a linear receiver. Thus, the receive equalizer vector can beselected as the column of V_(i) that corresponds to the highest singularvalue of Σ. For a typical singular value decomposition algorithm thesingular values will be sorted in descending order of the diagonal andthus the receive equalizer vector can be selected as the first column ofV_(i).

Thus, the singular value decomposition may be used by the scheduler 143to provide suitable estimates for the appropriate transmit beamformingand receive linear equalization that should be performed for a givenpropagation channel between the user equipment 101, 103 and base station105. The scheduling of the user equipments is then performed on thebasis of these estimates and specifically such that the linearequalization for user equipments in the same time-frequency resourceblock is as orthogonal as possible. However, it will be appreciated thatthe actual transmitters and receivers need not necessarily apply theseweights.

For example, although in some embodiments, the calculated transmitterweights may be communicated to the scheduled user equipments to use forthe uplink transmission, the actual weights may be determined by othermeans. Similarly, the receiver need not necessarily use the linearequalization indicated by the receive equalizer vector but may useanother receiving technique including e.g. a non-linear equalization.

Thus, the determined transmitter weights and receive equalizer vectormay be considered a scheduling estimate for the actual applied signalprocessing. However, in many embodiments, the determined estimates mayalso be fed to the appropriate transmitter/receiver and thus may be theactual weights used. Thus, the equalizer processor 133 may also be fedthe determined weights and use these to perform a linear equalizationfor the sharing user equipments.

As previously mentioned, the orthogonality processor 203 may determinethe orthogonality measure for two user equipments by determining theinner product between the receive equalizer vectors of the userequipments. The inner product may then be used directly as theorthogonality measure for the pair of user equipments or may beprocessed further to determine the orthogonality measure.

As a specific example, the two receive equalizer vectors may be given asv₁ and v₂ where:

${{v_{1}\begin{bmatrix}x_{1} \\{y_{1} + {\; z_{1}}}\end{bmatrix}}\mspace{14mu} v_{2}} = \begin{bmatrix}x_{2} \\{y_{2} + {\; z_{2}}}\end{bmatrix}$

In the specific example, the vectors are the receive vectors determinedfrom the appropriate (typically the first column of the matrix V ofsingular value decomposition of the appropriate channel matrices of thetwo user equipments. In this example, at least one component of eachvector may be a scalar value whereas the other will be a complex value.

The inner product for v₁ and v₂ can then be calculated as:

$\begin{matrix}{< {v_{1} \cdot v_{2}}>={v_{1}v_{2}^{\dagger}}} \\{= {{x_{1}x_{2}} + {y_{1}y_{2}} - {z_{1}z_{2}} + {\left( {{z_{1}y_{2}} - {y_{1}z_{2}}} \right)}}}\end{matrix}$

This value may in some embodiments be used directly as an orthogonalitymeasure.

In some embodiments, the orthogonality processor 203 may alternativelyor additionally use a different approach to determine the orthogonalitymeasure. Specifically, in this example the orthogonality processor 203may first calculate an orthogonal vector to the receive equalizer vectorof one of the user equipments of a set of user equipments. It may thenproceed to determine a distance measure between this orthogonal vectorand the receive equalizer vectors of other user equipments in the set.Thus, for a set comprising two user equipments, the orthogonal vector ofone of the receive equalizer vectors is first found and then a distancebetween this and the other receive equalizer vector is calculated. Itwill be appreciated that any suitable distance measure may be usedincluding specifically a distance measure that is easy to computethereby allowing a reduced complexity.

The distance measure may then be used to determine the orthogonalitymeasure. For example, the reciprocal value may be used in order toprovide an orthogonality measure that increases for increasingorthogonality.

Specifically, the orthogonal vector of a two component vector (thuscorresponding to two receive antennas) can readily be determine.Specifically, the orthogonal vector to v₁ is given by:

${v_{1}^{\bot} = \begin{bmatrix}{{- y_{1}} + {\; z_{1}}} \\x_{1}\end{bmatrix}}\mspace{14mu}$

Once the orthogonal vector v₁ ^(⊥) is calculated, the distance betweenthis vector and other vectors can be calculated e.g. as:

$\begin{matrix}{{d\left( {v_{2},v_{1}^{\bot}} \right)} = {\begin{bmatrix}{x_{2} + y_{1} - {\; z_{1}}} \\{y_{2} + {\; z_{2}} - x_{1}}\end{bmatrix}}^{2}} \\{= {\underset{= 1}{\underset{}{x_{1}^{2} + y_{1}^{2} + z_{1}^{2}}} + \underset{= 1}{\underset{}{x_{2}^{2} + y_{2}^{2} + z_{2}^{2}}} + {2\left( {{y_{1}x_{2}} - {x\; 1y_{2}}} \right)}}}\end{matrix}$

As the first two terms are constant and equal to unity for a singularvalue decomposition, the distance measure and thus the reciprocal (ore.g. sign inverted) orthogonality measure can simply be calculated as:

metric=2(x ₁ y ₂ −x ₂ y ₁)

This may thus result in a substantial reduction of the computationalload. Specifically, it requires only two multiplications and oneaddition in comparison to the inner product approach which requiresseven multiplications and four additions.

In some examples, the scheduler 143 may be arranged to allocate only asingle time-frequency resource block at a time and this may e.g. beallocated to the user equipment pair that has the highest orthogonalitymeasure. However, in most practical embodiments, the scheduler 143 isarranged to schedule a plurality of time-frequency resource blocks ineach scheduling interval.

In such embodiments, the scheduler 143 may be arranged to select aplurality of sets (specifically pairs) of user equipments for theplurality of time-frequency resource blocks. For example, in eachscheduling interval, the scheduler 143 may allocate M sets of userequipments to M time-frequency resource blocks.

In some such embodiments, the scheduler 143 may select the M sets byfirst generating a plurality of combinations of user equipments. Forexample, the scheduler 143 may generate all the possible combinations ofM sets of user equipments that do not include any repetitions of anindividual user equipment. Thus, these combinations may correspond toall feasible ways of allocating M sets of user equipments to the Mtime-frequency resource blocks without allocating any user equipmenttwice.

For each of the combinations, the scheduler may then calculate acombined orthogonality measure by combining the orthogonality measuresof all sets included in the combination. For example, the orthogonalitymeasures of the sets which are included in a combination may be added.

The scheduler 143 may then select a combination based on the combinedorthogonality measures and may specifically select the combination thatresults in the highest combined orthogonality measure. The Mtime-frequency resource blocks may then be allocated to the M sets ofuser equipments included in this combination.

In other embodiments, the required computational resource may besubstantially reduced by using an iterative and sequential approach.Specifically, the scheduler 143 may select a single set of userequipments as previously described. Specifically, the set of userequipments that has the highest orthogonality measure may be selectedand a time-frequency resource block may be allocated to this set.

The selected set may then be removed from the pool of candidate sets. Inaddition, any other sets containing a user equipment of the allocatedset may also be removed from the pool. The same process may then beiterated to select the next best set of user equipments from the reducedpool. The approach may then be repeated until all time-frequencyresource blocks have been allocated. Thus, specifically the process maybe repeated M times. Although, this approach may in some scenariosprovide less optimal scheduling than considering all possiblecombinations, it may substantially reduce the required computationalresource.

It will be appreciated that in different embodiments, different receiverequalizations may be applied by the equalization processor.Specifically, the equalization processor 133 may use a linearequalization wherein the equalization for each user equipment sharingthe time-frequency resource block is given by applying the weightscalculated by the singular value decomposition (and thus the weights ofthe receive equalizer vector).

For example, for user equipment k of a time-frequency resource block,the weights v_(k) ^(†) may be used resulting in:

${\hat{s}}_{k} = {{v_{k}^{\dagger}r} = {{\sqrt{P_{k}^{(s)}}\lambda_{k}s_{k}} + {v_{k}^{\dagger}{\sum\limits_{i \neq k}{\sqrt{P_{i}^{(s)}}\lambda_{i}v_{i}s_{i}}}} + {v_{k}^{\dagger}n}}}$

As the scheduling algorithm seeks to make v_(k) and v_(i) as orthogonalas possible, the second term in the above equation will be minimized andmay often be close to zero. Thus, in many systems the schedulingapproach applied may make it feasible to use simple linear equalizationfor receiving signals from multiple user equipments sharing a giventime-frequency resource block.

More specifically, it can be shown that the throughput can be determinedas:

$\begin{matrix}{C = {\log_{2}\left( {1 + {SINR}} \right)}} \\{= {\log_{2}\left( {1 + \frac{P_{k}^{(s)}\lambda_{k}^{2}}{{P_{i}^{(s)}\lambda_{i}^{2}P\; v_{k}^{\dagger}v_{i}P^{2}} + P^{(n)}}} \right)}}\end{matrix}$

where Pv_(k) ^(†)v_(i)P² will typically be a very low due to theallocation approach.

Thus, this approach provides the advantages of reduced complexity andcomputational resource demand while providing low interference.

It will be appreciated that the equalization processor 133 may use otherapproaches. For example, the equalization processor 133 may apply aMinimum Mean Squared Error (MMSE) equalizer as will be known to theperson skilled in the art.

In such an example, the resulting output signal for user equipment k maybe given by:

${\hat{s}}_{k} = {{g_{k}^{\dagger}r} = {{\sqrt{P_{k}^{(s)}}\lambda_{k}g_{k}^{\dagger}v_{k}s_{k}} + {g_{k}^{\dagger}{\sum\limits_{i \neq k}{\sqrt{P_{i}^{(s)}}\lambda_{i}v_{i}s_{i}}}} + {g_{k}^{\dagger}n}}}$

where

$g_{k} = {\left( {{\lambda_{i}^{2}v_{k}v_{k}^{\dagger}} + {\frac{P^{(n)}}{P_{k}^{(s)}}I}} \right)^{- 1}\lambda_{i}v_{i}}$

As other examples, the equalization processor 133 may use Joint MMSE orSuccessive Interference Cancellation (SIC).

The use of the more complex receiver equalization may in some scenariosprovide improved performance. However, as the scheduling may be based onan assumption of linear equalization, this improvement may be relativelylimited. Furthermore, by basing the scheduling on a more simple linearequalization assumption, the computational resource demand may bereduced substantially.

FIG. 3 illustrates an example of a method of operation for a MIMOcommunication system in accordance with some embodiments of theinvention. The method initiates in step 301 wherein a receive equalizervector is determined for a MIMO receiver for each of a plurality of userequipments in response to a channel matrix for the user equipment.

Step 301 is followed by step 303 wherein orthogonality measures betweenreceive equalizer vectors of user equipments in a set of user equipmentsis determined for a plurality of sets of user equipments. Each setcomprises at least two user equipments of the plurality of userequipments. Step 303 is followed by step 305 wherein at least a firstset of user equipments is selected from the plurality of sets of userequipments to be allocated a shared MIMO air interface resource inresponse to the orthogonality measures. Step 305 is followed by step 307wherein the shared MIMO air interface resource is allocated to the firstset of user equipments for simultaneous MIMO communication.

It will be appreciated that the above description for clarity hasdescribed embodiments of the invention with reference to differentfunctional units and processors. However, it will be apparent that anysuitable distribution of functionality between different functionalunits or processors may be used without detracting from the invention.For example, functionality illustrated to be performed by separateprocessors or controllers may be performed by the same processor orcontrollers. Hence, references to specific functional units are only tobe seen as references to suitable means for providing the describedfunctionality rather than indicative of a strict logical or physicalstructure or organization.

The invention can be implemented in any suitable form includinghardware, software, firmware or any combination of these. The inventionmay optionally be implemented at least partly as computer softwarerunning on one or more data processors and/or digital signal processors.The elements and components of an embodiment of the invention may bephysically, functionally and logically implemented in any suitable way.Indeed the functionality may be implemented in a single unit, in aplurality of units or as part of other functional units. As such, theinvention may be implemented in a single unit or may be physically andfunctionally distributed between different units and processors.

Although the present invention has been described in connection withsome embodiments, it is not intended to be limited to the specific formset forth herein. Rather, the scope of the present invention is limitedonly by the accompanying claims. Additionally, although a feature mayappear to be described in connection with particular embodiments, oneskilled in the art would recognize that various features of thedescribed embodiments may be combined in accordance with the invention.In the claims, the term comprising does not exclude the presence ofother elements or steps.

Furthermore, although individually listed, a plurality of means,elements or method steps may be implemented by e.g. a single unit orprocessor. Additionally, although individual features may be included indifferent claims, these may possibly be advantageously combined, and theinclusion in different claims does not imply that a combination offeatures is not feasible and/or advantageous. Also the inclusion of afeature in one category of claims does not imply a limitation to thiscategory but rather indicates that the feature is equally applicable toother claim categories as appropriate. Furthermore, the order offeatures in the claims does not imply any specific order in which thefeatures must be worked and in particular the order of individual stepsin a method claim does not imply that the steps must be performed inthis order. Rather, the steps may be performed in any suitable order.

1. A Multiple In Multiple Out, MIMO, communication system comprising: avector processor for determining a receive equalizer vector for a MIMOreceiver for each of a plurality of user equipments in response to achannel matrix for the user equipment; an orthogonality processor fordetermining, for a plurality of sets of user equipments, orthogonalitymeasures between receive equalizer vectors of user equipments in theset, each set comprising at least two user equipments of the pluralityof user equipments; a selection processor for selecting at least a firstset of user equipments from the plurality of sets of user equipments tobe allocated a shared MIMO air interface resource in response to theorthogonality measures; and an allocation processor for allocating theshared MIMO air interface resource to the first set of user equipmentsfor simultaneous MIMO communication.
 2. The MIMO communication system ofclaim 1 wherein the receive equalizer vector of a user equipment isindicative of weights applied to receive antennas of the MIMO receiverfor the user equipment.
 3. The MIMO communication system of claim 1wherein the vector processor is arranged to perform a singular valuedecomposition of the channel matrix for each of a plurality of userequipments, the singular value decomposition providing a set of singularvalue decomposition values, a set of first single value decompositionvectors associated with transmitter antenna weights and a set of secondsingle value decomposition vectors associated with receiver antennaweights; and to select the receive equalizer vector as a vector of theset of second single value decomposition vectors associated withreceiver antenna weights.
 4. The MIMO communication system of claim 3wherein the vector processor is arranged to select the receive equalizervector as a vector of the set of second single value decompositionvectors associated with receiver antenna weights corresponding to asingular value decomposition value of the set of singular valuedecomposition values having a highest value.
 5. The MIMO communicationsystem of claim 1 wherein each of the plurality of sets of userequipments contain two user equipments.
 6. The MIMO communication systemof claim 1 wherein the selection processor is arranged to select thefirst set of user equipments as the set of user equipments having ahighest orthogonality measure.
 7. The MIMO communication system of claim1 wherein the orthogonality processor is arranged to determine an innerproduct between receive equalizer vectors of at least one pair of userequipments of at least one set of the plurality of sets of userequipments; and to determine the orthogonality measure for the at leastone set in response to the inner product.
 8. The MIMO communicationsystem of claim 1 wherein the orthogonality processor is arranged to:determine an orthogonal vector of the receive equalizer vector of afirst user equipment of at least one set of the plurality of sets ofuser equipments; determine a distance measure between the orthogonalvector and a receive equalizer vector of at least one other userequipment of the at least one set; and determining an orthogonalitymeasure for the at least one set in response to the distance measure. 9.The MIMO communication system of claim 1 arranged to allocate sharedMIMO air interface resource blocks to each of a plurality of selectedsets of the plurality of sets of user equipments by iterativelyselecting a selected set of user equipments and removing the selectedset from the plurality of sets of user equipments.
 10. The MIMOcommunication system of claim 1 wherein the selection processor isarranged to select a plurality of sets of user equipments for aplurality of shared MIMO air interface resource blocks by, for aplurality of combinations of sets of user equipments, determining acombined orthogonality measure in response to orthogonality measures ofsets of user equipments included in the combination; and to select afirst combination of the plurality of combinations in response to thecombined orthogonality measures; and the allocation processor isarranged to allocate a shared MIMO air interface resource block to eachset of the first combination.
 11. The MIMO communication system of claim1 wherein the shared MIMO air interface resource is an uplink resource.12. The MIMO communication system of claim 1 wherein the MIMO receiveris a receiver of a MIMO base station of the MIMO communication system.13. The MIMO communication system of claim 1 wherein the MIMO receivercomprises a linear equalizer for differentiating between transmissionsin the shared MIMO air interface resource from user equipments of thefirst set.
 14. A scheduler for a Multiple In Multiple Out, MIMO,communication system, the scheduler comprising: a vector processor fordetermining a receive equalizer vector for a MIMO receiver for each of aplurality of user equipments in response to a channel matrix for theuser equipment; an orthogonality processor for determining, for aplurality of sets of user equipments, orthogonality measures betweenreceive equalizer vectors of user equipments in the set, each setcomprising at least two user equipments of the plurality of userequipments; a selection processor for selecting at least a first set ofuser equipments from the plurality of sets of user equipments to beallocated a shared MIMO air interface resource in response to theorthogonality measures; and an allocation processor for allocating theshared MIMO air interface resource to the first set of user equipmentsfor simultaneous MIMO communication.
 15. A method of operation for aMultiple In Multiple Out, MIMO, communication system, the methodcomprising: determining a receive equalizer vector for a MIMO receiverfor each of a plurality of user equipments in response to a channelmatrix for the user equipment; determining, for a plurality of sets ofuser equipments, orthogonality measures between receive equalizervectors of user equipments in the set, each set comprising at least twouser equipments of the plurality of user equipments; selecting at leasta first set of user equipments from the plurality of sets of userequipments to be allocated a shared MIMO air interface resource inresponse to the orthogonality measures; and allocating the shared MIMOair interface resource to the first set of user equipments forsimultaneous MIMO communication.